We are proud of the quality of our doctoral students and the training they receive. As an Electrical Engineering PhD candidate in our department, you will share in the excitement of discovery as you collaborate with our faculty on cutting-edge research. You will also acquire strong independent research skills and begin to develop your reputation within your area’s larger research community.
Because the advisor-graduate relationship is the cornerstone of a successful PhD experience, all new PhD candidates are carefully matched with faculty advisors, based on mutual research interests.
You will find the work here challenging and personally rewarding. Students who complete our PhD program are well-prepared for careers in academia, research, government and industry.
While pursuing an Electrical Engineering doctoral degree from the ECE department, it will be important to keep in mind the Program’s Requirements so as to be sure that you are on track to graduate. The final step during the process is defending a dissertation, which requires a lot of preparation before presenting.
Visit our Graduate Admission Information page for application requirements, deadlines, and other important information.
Mentoring and Annual Discussions Policies
Current ECE doctoral candidates are encouraged to review the university's mentoring and professional development policies.
Student Spotlight
Arik Slepyan Receives ARCS/MWC Chapter Scholar Award
The $15,000 award recognizes graduate student Slepyan’s exceptional potential to contribute to breakthrough technologies and discoveries in science, technology, engineering, and medical research. Learn MoreAkwasi Akwaboah Receives NSF Fellowship Award
This fellowship supports a collaborative exchange between Ph.D. candidate Akwaboah’s home lab, the Computational Sensory Motor Systems lab led by ECE Professor Ralph Etienne-Cummings, and the University of California San Diego (UCSD) Integrated Systems Neuroengineering lab, directed by Gert Cauwenberghs. Learn MoreHopkins Engineers Chat with ChatGPT4 to Design Brain-Inspired Chips
Graduate student Michael Tomlinson and team pioneer a new approach to creating neural network chips—neuromorphic accelerators that could power energy-efficient, real-time machine intelligence for next-generation embodied systems like autonomous vehicles and robots. Learn More“We are capturing interactions between brain activity and genetic mutations associated with schizophrenia and fusing these views into a single framework. ”